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q01_read_csv_data_to_df/build.py

@@ -5,4 +5,6 @@
 path = "data/ipl_dataset.csv"
 
 # Solution
-
+def read_csv_data_to_df(path):
+    df = pd.read_csv(path)
+    return df

q02_get_unique_values/build.py

@@ -4,3 +4,6 @@
 ipl_df = read_csv_data_to_df("data/ipl_dataset.csv")
 
 #Solution
+def get_unique_venues():
+    venues = ipl_df['venue'].unique()
+    return venues

q03_get_run_counts/build.py

@@ -5,4 +5,6 @@
 ipl_df = read_csv_data_to_df("./data/ipl_dataset.csv")
 
 # Solution
-
+def get_run_counts():
+    counts = ipl_df['runs'].value_counts()
+    return counts

q04_get_match_specific_df/build.py

@@ -4,4 +4,5 @@
 ipl_df = read_csv_data_to_df("./data/ipl_dataset.csv")
 
 # Solution
-
+def get_match_specific_df(match_code):
+    return ipl_df[ipl_df['match_code'] == match_code]

q05_create_bowler_filter/build.py

@@ -5,3 +5,5 @@
 ipl_df = read_csv_data_to_df("./data/ipl_dataset.csv")
 
 # Solution
+def create_bowler_filter(bowler):
+    return ipl_df['bowler'] == bowler

q06_get_match_innings_runs/build.py

@@ -5,7 +5,5 @@
 ipl_df = read_csv_data_to_df("data/ipl_dataset.csv")
 
 # Solution
-
-
-
-
+def get_match_innings_runs():
+    return ipl_df.groupby(['match_code','inning'])['runs'].sum()

q07_get_run_counts_by_match/build.py

@@ -5,3 +5,5 @@
 ipl_df = read_csv_data_to_df("./data/ipl_dataset.csv")
 
 # Solution
+def get_runs_counts_by_match():
+    return ipl_df.pivot_table(index='match_code',columns='runs',aggfunc='count')['batsman']